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Release 8.2.2

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Computes the standard deviation across column values of Integer or Decimal type using the sample statistical method.

The standard deviation of a set of values attempts to measure the spread in values around the mean and is used to measure confidence in statistical results. A standard deviation of zero means that all values are the same, and a small standard deviation means that the values are closely bunched together. A high value for standard deviation indicates that the numbers are spread out widely. Standard deviation is always a positive value.

NOTE: This function applies to a sample of the entire population. More information is below.

Relevant terms:

Term Description
Population Population statistical functions are computed from all possible values. See https://en.wikipedia.org/wiki/Statistical_population.
Sample

Sample-based statistical functions are computed from a subset or sample of all values. See https://en.wikipedia.org/wiki/Sampling_(statistics).

These function names include `SAMP` in their name.

NOTE: Statistical sampling has no relationship to the samples taken within the product. When statistical functions are computed during job execution, they are applied across the entire dataset. Sample method calculations are computed at that time.

• This function is calculated across a sample of all values.

• For more information on a population version of this function, see STDEV Function.

If a row contains a missing or null value, it is not factored into the calculation. If no numeric values are detected in the input column, the function returns `0`.

The square of standard deviation is variance. See VAR Function.

For a version of this function computed over a rolling window of rows, see ROLLINGSTDEV Function.

Wrangle vs. SQL: This function is part of Wrangle , a proprietary data transformation language. Wrangle is not SQL. For more information, see Wrangle Language.

## Basic Usage

stdevsamp(myRating)

Output: Returns the standard deviation of the values from the `myRating` column using the sample method of calculation.

## Syntax and Arguments

stdevsamp(col_ref) [group:group_col_ref] [limit:limit_count]

ArgumentRequired?Data TypeDescription
function_col_refYstringName of column to which to apply the function

For more information on the `group` and `limit` parameters, see Pivot Transform.

For more information on syntax standards, see Language Documentation Syntax Notes.

### col_ref

Name of the column whose values you wish to use in the calculation. Column must be a numeric (Integer or Decimal) type.

• Literal values are not supported as inputs.
• Multiple columns and wildcards are not supported.

Usage Notes:

Required?Data TypeExample Value
YesString (column reference)`myValues`

## Examples

Tip: For additional examples, see Common Tasks.

This example shows some of the statistical functions that use the sample method of computation. These include:
• `STDEVSAMP` - computes standard deviation using the sample method. See STDEVSAMP Function.
• `VARSAMP` - computes variance using the sample method. See VARSAMP Function.
• `STDEVSAMPIF` - computes standard deviation based on a condition and using the sample method. See STDEVSAMPIF Function.
• `VARSAMPIF` - computes standard deviation based on a condition and using the sample method. See VARSAMPIF Function

Source:

Students took tests on three consecutive Saturdays:

StudentDateScore
Andrew11/9/1981
Bella11/9/1984
Christina11/9/1979
David11/9/1964
Ellen11/9/1961
Fred11/9/1963
Andrew11/16/1973
Bella11/16/1988
Christina11/16/1978
David11/16/1967
Ellen11/16/1987
Fred11/16/1990
Andrew11/23/1976
Bella11/23/1993
Christina11/23/1981
David11/23/1997
Ellen11/23/1997
Fred11/23/1991

Transformation:

You can use the following transformations to calculate standard deviation and variance across all dates using the sample method. Each computation has been rounded to three digits.

Transformation Name `New formula` `Single row formula` `round(stdevsamp(Score), 3)` `'stdevSamp'`

Transformation Name `New formula` `Single row formula` `round(varsamp(Score), 3)` `'varSamp'`

You can use the following to limit the previous statistical computations to the last two Saturdays of testing:

Transformation Name `New formula` `Single row formula` `round(stdevsampif(Score, Date != '11\/9\/2019'), 3)` `'stdevSampIf'`

Transformation Name `New formula` `Single row formula` `round(varsampif(Score, Date != '11\/9\/2019'), 3)` `'varSampIf'`

Results:

StudentDateScorevarSampIfstdevSampIfvarSampstdevSamp
Andrew11/9/198194.5159.722131.67311.475
Bella11/9/198494.5159.722131.67311.475
Christina11/9/197994.5159.722131.67311.475
David11/9/196494.5159.722131.67311.475
Ellen11/9/196194.5159.722131.67311.475
Fred11/9/196394.5159.722131.67311.475
Andrew11/16/197394.5159.722131.67311.475
Bella11/16/198894.5159.722131.67311.475
Christina11/16/197894.5159.722131.67311.475
David11/16/196794.5159.722131.67311.475
Ellen11/16/198794.5159.722131.67311.475
Fred11/16/199094.5159.722131.67311.475
Andrew11/23/197694.5159.722131.67311.475
Bella11/23/199394.5159.722131.67311.475
Christina11/23/198194.5159.722131.67311.475
David11/23/199794.5159.722131.67311.475
Ellen11/23/199794.5159.722131.67311.475
Fred11/23/199194.5159.722131.67311.475